Chelsea Lindley

March 18, 2008

GEOG 370

Lab 4(12.5/14)

PART 1

  1. No. The points have a higher level of abstraction, because they can vary in size and shape, representing large or small cities as general circles, triangles, etc. However, lines represent exact locations of roads, with little variation from reality, and little deviation from one another. For example, in representing the City data layer, the dots could be huge or tiny, circles or squares. However, they still all represent a city … just in various ways. On the other hand, there was little variation in the lines of the Roads data layer. The lines showed exactly where the roads were located, and a change in thickness was not made.

Say that the points now represent parks and the lines now represent rivers. The same applies – the points have a higher level of abstraction because they can vary (size, shape, etc.) so much in comparison to the lines.

Point: one or a series of points; example: cities, building

Line: collection of points; example: highway, streams

  1. The identify tool provides you with specific location names, fields, and values of the spot on the map that you choose to identify. The option to change the layers being identified is very useful, because it allows you to view information about one layer at a time, or several at a time if you choose. This way you have the option of what information you are given, according to what you need.
  2. You must differentiate between text and numeric data types, because if you chose numeric you’d be typing in only numbers. Also, these data types have different types of precision that are associated with them. The precisions associated with numeric data are not needed for this lab; text data is what is needed. The field width must be specified, because that is what specifies how many characters can be typed in a certain field. If you need to type 20 characters and the field width is 8, then you won’t be able to type what is needed (it’ll cut you short). Therefore, you must choose an appropriate width according to the needs of each field.
  3. Data from the weather table is now there (including ID#, the states I selected, and the weather for those states). If I didn’t choose to add data about a state (in the weather table), then the fields for those “unchosen” states read “Null.”
  4. The original States layer data start their column titles with “States.” and the new Weather data start their column titles with “Weather.”.
  5. There would be too many states to join to the selected weather data. (There were only 11 weather states selected, but 50 actual states ... so, there would not be spots for the other 39 states to join to.)

(-0.5) Because one is spatial data(States) and one is not, the join would not work.

  1. The selected weather records are shown below.
  1. The new attribute table is shown below.

PART 2

  1. Reclassifying allows one to assign new scores to the different distances. By assigning new scores, the legend and map are easier to read and interpret.
  2. The map tells you that the developer should build in the area with the highest score, and shows you where these areas are located. The highest scores represent areas closest to the major roads and farthest from creeks and streams. The lowest scores represent areas farthest from the major roads and closest to creeks and streams.

3. Step 4 classifies zones in Chapel Hill, assigning them a value of 1 if the zone is where the client has requested to build (“office/institutional” or “mixed use and office/institutional”), and a value of 0 of the zone is not where the client has requested to build. This makes it easy to see which areas on the map meet the client’s building criteria (zone 1 areas). It combines suitability data with zoning data in order to find out the final criteria of locations in an office zone with our desired distances in regards to roads and water.

  1. In determining the locations that would be the best choices for your office, I took all of your criteria into consideration. I located major roads in Chapel Hill and devised a map showing zones that were closest to these roads, as well as zones that were farthest from these roads. On a scale of 1-10, I labeled the zones closest to the major roads a 10. I also located all creeks and streams in Chapel Hill and devised a map showing zones that were closest to these water areas, as well as zones that were farthest from these waterways. On a scale of 1-10, I labeled the zones farthest from the waterways a 10. I then combined the two maps. In combining the maps, I also combined the scales. Therefore, on the combined map, the higher the score (20 being the highest), the more suitable the location based on your criteria (close to major roads and far away from creeks and streams).

I then devised a map that showed areas in Chapel Hill that were located within Chapel Hill’s Office/Institutional or Mixed-Use and Office/Institutional zoning districts, as well as areas outside of these districts. I labeled areas in these districts a 1 and areas outside of these districts a 0. By combining this map with the previously devised map, I was able to find the area in Chapel Hill that is in the districts you requested, farthest from creeks or streams, and closest to major roads. The area I located that would be best for your building location (based on the criteria you gave me) is at the intersection of Dobbins Rd. and Sage Rd. The area also overlaps Durham-Chapel Hill Rd. slightly. Nice statement!

Your three maps really look nice, but you have to include north arrow and scale bar for the perfect cartographic visualization. (-1.0)